Generative modeling of single-cell time series with PRESCIENT enables prediction of cell trajectories with interventions
Single-cell RNA-Seq allows us to observe snapshots of how biological systems change over time at cellular resolution. Here, the authors develop a generative framework that uses time-resolved single-cell data to model how cells change in physical time, including in response to perturbations.
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Auteurs principaux: | , , |
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Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2021
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Accès en ligne: | https://doaj.org/article/197cf2be15834f71b3824cd58fa503a3 |
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